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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 27, No 2: August 2022" : 64 Documents clear
Dual embedding with input embedding and output embedding for better word representation Yoonjoo Ahn; Eugene Rhee; Jihoon Lee
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp1091-1099

Abstract

Recent studies in distributed vector representations for words have variety of ways to represent words. We propose a various ways using input embedding and output embedding to better represent words than single model. We compared the performance in terms of word analogy and word similarity with each input and output embeddings and various dual embeddings which are the combination of those two embeddings. Performance evaluation results show that the proposed dual embeddings outperform each single embedding, especially with the way of simply adding input and output embeddings. We figured out two things in this paper, i) not only input embedding but also output embedding has such meaning to represent the words and ii) combining input embedding and output embedding as dual embedding outperforms the single embedding when we use input embedding and output embedding individually.
A recommendation system of training data selection method for cross-project defect prediction Benyamin Langgu Sinaga; Sabrina Ahmad; Zuraida Abal Abas; Intan Ermahani A. Jalil
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp990-1006

Abstract

Cross-project defect prediction (CPDP) has been a popular approach to address the limited historical dataset when building a defect prediction model. Directly applying cross-project datasets to learn the prediction model produces an unsatisfactory predictive model. Therefore, the selection of training data is essential. Many studies have examined the effectiveness of training data selection methods, and the best-performing method varied across datasets. While no method consistently outperformed the others across all datasets, predicting the best method for a specific dataset is essential. This study proposed a recommendation system to select the most suitable training data selection method in the CPDP setting. We evaluated the proposed system using 44 datasets, 13 training data selection methods, and six classification algorithms. The findings concluded that the recommendation system effectively recommends the best method to select training data.
Respiratory failure in COVID-19 patients a comparative study of smokers to nonsmokers Mohammad Kharabsheh; Shadi Banitaan; Hakam W. Alomari; Mohammad Alshirah; Sukaina Alzyoud
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp1127-1137

Abstract

For many decades, smoking tobacco has been a crucial concern due to respiratory failure. The potential relationship between smoking and COVID-19 has been recently investigated. In this paper, we study and investigate the role of the decision support system to predict the ratio of respiratory failure in smokers versus non-smokers among COVID-19 patients. We employed a classifier that predicts the ratio of respiratory failure as well as the ratio of the death toll between smokers and non-smokers using machine learning methods. The employed model demonstrate a prediction accuracy of 77% when applied on a sample from 23 countries that confirmed the highest number of COVID-19 patients. This was obtained from The World Bank Data-Health Nutrition and Population Statistics. As a result, a strong (significant) relationship between smoking tobacco and COVID-19 was illustrated by the employed model. Our approach achieves a good recall (78%). Thus, smokers are more susceptible to respiratory failure than non-smokers, as COVID-19 complications.
Brain seizures detection using machine learning classifiers based on electroencephalography signals: a comparative study Atef Hashem Attia; Ashraf Mahroos Said
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp803-810

Abstract

The paper demonstrates various machine learning classifiers, they have been used for detecting epileptic seizures quickly and accurately through electroencephalography (EEG), in real time. Symptoms of epilepsy are caused abnormal brain activity. Analyzing and detecting epileptic seizures presents many challenges because EEG signals are non-stationary, and the patterns of the seizure vary for each patient. Moreover, the EEG signals are noisy, and this affect the process of seizure detection. On the other hand, Machine learning algorithms are very accurate, adaptive and generalize very well when provided with diverse and big training data and can easily analyze complex structure of the EEG signal despite the noisiness when compared to other methods. With this approach the features of epileptic seizures can be learned and used to correctly identify other seizure cases. The demonstration states a comparison between various classifiers, including random forests, K-nearest neighbors (K-NN), decision trees, support vector machine (SVM), logistic regression and naïve bayes. Different performance metrics is used such as accuracy, receiver operating characteristics (ROC), mean absolute error (MAE), root-mean-square error (RMSE) and most importantly detection time for each algorithm. The Bonn university dataset has been used for demonstration process for the classification of the epileptic seizure.
Graphene-polyvinyl alcohol polymer based saturable absorption at 2000 nm region Nabihah Hussin; Asrul Izam Azmi; Mohd Rashidi Salim; Muhammad Yusof Mohd Noor; Ahmad Sharmi Abdullah; Michael David; Fauzan Ahmad; Mohd Haniff Ibrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp701-708

Abstract

A graphene-polyvinyl alcohol (PVA) composite saturable absorption is demonstrated at 2000 nm region. Graphene suspension is produced using low-cost electrochemical exfoliation process. The suspension is mixed with PVA host polymer in 1:1 ratio and left evaporated at room temperature which finally produced graphene-PVA thin film. Thulium doped fiber (TDF) gain medium has been shown to produce a stable Q-switched pulse with a highest repetition rate of 54 kHz, a short pulse duration of 2.89 µs, a maximum peak power of 16 mW, and an estimated maximum pulse energy of 49 nJ. Apparently, at 2000 nm region, superior performances of graphene-PVA composite have been recorded which was largely contributed by meticulous composite preparation and homogenous mixture with PVA host.
Applying the green Ca2Al3O6F:Eu2+ oxyfluoride phosphorus on white emitting diodes Van Liem Bui; Dieu An Nguyen Thi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp754-759

Abstract

Ca2Al3O6F:Eu2+, a new green-emitting and its photoluminescence (PL) characteristics for white-emitting diodes, have been analyzed and generated (w-LEDs). This phosphorus displays a strong absorption range between ultraviolet (UV) and blue region, along with a wide green emission range of 502 nm. The procedure for concentration suppression and Eu2+ luminous longevity has been investigated using Ca2Al3O6F:Eu2+ phosphors. Key characteristics for manufacturing w-LED lamps, such as photoluminesce based on temperature, microstructure, morphology, CIE value and quantum efficiency, were also investigated in Ca2Al3O6F:Eu2+. The findings show that Ca2Al3O6F:Eu2+, is a suitable option for almost UV-excited w-LEDs as a green component.
Application of advanced encryption standard in the computer or handheld online year-round registration system Jomar L. Calpito; Paul L. Olanday; Alain C. Gallarde
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp922-935

Abstract

With various severe security threats for web applications, ensuring security on the database layer itself is imperative. Hence, this study aims to protect data saved on the computer or handheld online year-round (CHOY) registration system using the advanced encryption standard (AES) to strengthen data security within the app so that even potential attackers gain access to the app's database; they cannot obtain valuable information because it is scrambled and unreadable. The proponents based the study's conceptual framework on the symmetric and asymmetric key algorithms and procedures manual on enrollment of Southern Isabela College of arts and trades (SICAT) and ISO 25010. The study consists of three elements: developing the CHOY web app imbued with AES, testing it in terms of online registration and spam prevention, and evaluating it using the ISO 25010 in terms of compatibility, reliability, and security. The evaluation results show that implementing the AES in the CHOY web app meets the ISO 25010 criteria mentioned above.
Utilizing a strait-range green phosphor γ-AlON:Mn,Mg for the task of achieving a super-broad hue gamut display My Hanh Nguyen Thi; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp748-753

Abstract

The screen backlighting produced by green β-sialon:Eu, as well as red K2SiF6:Mn phosphors, have an extremely expansive hue gamut that encompasses the majority of the national television system committee (NTSC) triangle. For our research, a substitute phosphor in green would be probed in terms of improving the screen hue range even further. The phosphor γ-AlON:Mn,Mg appears to be green in color with a smaller radiation band of colors than sharp β-silaon:Eu. By replacing γ-AlON:Mn,Mg with β-sialon:Eu, the screen hue range in the blue-green area is significantly expanded. In both the CIE 1931 and CIE 1976 hue spaces, the hue range of screens with γ-AlON:Mn,Mg, and K2SiF6:Mn entirely surpasses the NTSC benchmark. Furthermore, the stability of LEDs emit white light using γ-AlON:Mn,Mg appears to be similar to LEDs that utilize β-sialon:Eu.
Cluster-based fuzzy regression trees for software cost prediction Assia Najm; Abdelali Zakrani; Abdelaziz Marzak
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp1138-1150

Abstract

The current paper proposes a novel type of decision tree, which is never used for software development cost prediction (SDCP) purposes, the cluster-based fuzzy regression tree (CFRT). This model uses the fuzzy k-means (FKM), which deals with data uncertainty and imprecision. The tree expansion is based on the variability measure by choosing the node with the highest value of granulation diversity. This paper outlined an experimental study comparing CFRT with four SDCP methods, notably linear regression, multi-layer perceptron, K-nearest-neighbors, and classification and regression trees (CART), employing eight datasets and the leave-one-out cross-validation (LOOCV). The results show that CFRT is among the best, ranked first in 3 datasets according to four accuracy measures. Also, according to the Pred(25%) values, the proposed CFRT model outperformed all the twelve compared techniques in four datasets: Albrecht, constructive cost model (COCOMO), Desharnais, and The International Software Benchmarking Standards Group (ISBSG) using LOOCV and 30-fold cross-validation technique.
Investigation of MAl2−xSixO4−xNx:Eu2+ phosphor for improving luminescence properties of white LEDs Thanh Binh Ly; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp626-631

Abstract

We implement a solid-state reaction technique to make MAl2−xSixO4−xNx (M = Ca, Sr, Ba) as well as its variant doped with Eu at 1300 – 1400°C in a nitrogen hydrogen environment. Then, we measure the solubility of (SiN)+ in MAl2O4. By replacing (AlO)+ with (SiN)+, whose solubility is dependent on M cations, nitrogen may be integrated into MAl2O4. (SiN)+ has poor solubility in CaAl2O4 (x ≈ 0.025) and SrAl2O4 lattices (x ≈ 0.045) but a considerable integrated quantity of (SiN)+ against BaAl2O4 (x ≈ 0.6). Because of the low solubility of (SiN)+, incorporation of (SiN)+ barely affects the luminescence characteristics of MAl2O4 when doped with Eu2+ (M = Ca, Sr), resulting in discharges in green as well as blue at nearly constant wavelengths measured at 440 as well as 515 nm, respectively. With certain concentrations of (SiN)+ as well as Eu2+, Eu2+-doped BaAl2−xSixO4−xNx emits one wide green discharge line under a maximum within the region 500 – 526 nm. Furthermore, once we add nitrogen, both the excitation as well as discharge lines for Eu2+ exhibit one substantial redshift. BaAl2−xSixO4−xNx: Eu2+ is a compelling transmuting phosphor that can be utilized for WLED devices because of its efficient stimulation in the range of 390–440 nm radiation.

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